from __future__ import annotations

import json
import re

from sqlalchemy.orm import Session

from app.core.agent_enums import AgentAssetStatus, AgentAssetType
from app.schemas.agent_asset import AgentAssetListItem
from app.schemas.user_agent import (
    UserAgentCitation,
    UserAgentDraftPayload,
    UserAgentRequest,
    UserAgentResponse,
    UserAgentSuggestedAction,
)
from app.services.agent_assets import AgentAssetService
from app.services.agent_foundation import AgentFoundationService
from app.services.runtime_chat import RuntimeChatService

SCENARIO_LABELS = {
    "expense": "报销",
    "accounts_receivable": "应收",
    "accounts_payable": "应付",
    "knowledge": "知识",
    "unknown": "通用",
}

RISK_REASON_MAP = {
    "duplicate_expense": "检测到同员工、同金额或近似单据存在重复提交迹象。",
    "amount_over_limit": "金额超过当前制度或预算阈值，需要补充例外说明。",
    "invoice_anomaly": "票据或附件完整性不满足当前规则要求，需要补件或人工复核。",
    "ar_overdue": "应收账款已出现逾期，存在回款延迟风险。",
    "ap_overdue": "应付付款已出现逾期，可能影响供应商履约或合作关系。",
}

GENERIC_EXPENSE_PROMPTS = {
    "报销",
    "我要报销",
    "我想报销",
    "帮我报销",
    "我要申请报销",
    "发起报销",
    "提交报销",
}

EXPLICIT_DRAFT_KEYWORDS = ("生成", "草稿", "起草", "创建", "发起", "准备")

EXPENSE_TYPE_LABELS = {
    "travel": "差旅",
    "hotel": "住宿",
    "transport": "交通",
    "meal": "餐费",
    "meeting": "会务",
    "entertainment": "招待",
}


class UserAgentService:
    def __init__(self, db: Session) -> None:
        self.db = db
        self.asset_service = AgentAssetService(db)
        self.runtime_chat_service = RuntimeChatService(db)

    def respond(self, payload: UserAgentRequest) -> UserAgentResponse:
        AgentFoundationService(self.db).ensure_foundation_ready()
        citations = self._build_rule_citations(payload)
        suggested_actions = self._build_suggested_actions(payload)
        risk_flags = self._resolve_risk_flags(payload)
        draft_payload = (
            self._build_draft_payload(payload)
            if payload.ontology.intent == "draft"
            else None
        )

        if payload.degraded and payload.tool_payload.get("message"):
            return UserAgentResponse(
                answer=str(payload.tool_payload["message"]),
                citations=citations,
                suggested_actions=suggested_actions,
                risk_flags=risk_flags,
                requires_confirmation=payload.requires_confirmation,
            )

        guided_answer = self._build_guided_answer(payload)
        if guided_answer:
            return UserAgentResponse(
                answer=guided_answer,
                citations=citations,
                suggested_actions=suggested_actions,
                draft_payload=draft_payload,
                risk_flags=risk_flags,
                requires_confirmation=payload.requires_confirmation,
            )

        fallback_answer = self._build_fallback_answer(
            payload,
            citations=citations,
            draft_payload=draft_payload,
        )
        answer = self._generate_answer_with_model(
            payload,
            citations=citations,
            suggested_actions=suggested_actions,
            risk_flags=risk_flags,
            draft_payload=draft_payload,
            fallback_answer=fallback_answer,
        )

        return UserAgentResponse(
            answer=answer or fallback_answer,
            citations=citations,
            suggested_actions=suggested_actions,
            draft_payload=draft_payload,
            risk_flags=risk_flags,
            requires_confirmation=payload.requires_confirmation,
        )

    def _build_fallback_answer(
        self,
        payload: UserAgentRequest,
        *,
        citations: list[UserAgentCitation],
        draft_payload: UserAgentDraftPayload | None,
    ) -> str:
        if payload.ontology.intent in {"query", "compare"}:
            return self._build_query_answer(payload)

        if payload.ontology.intent == "risk_check":
            return self._build_risk_answer(payload, citations)

        if payload.ontology.intent == "draft" and draft_payload is not None:
            return (
                f"已生成 {draft_payload.title}，当前仅返回待人工确认的草稿内容，"
                "仍需人工确认后再进入正式流程。"
            )

        return self._build_explain_answer(payload, citations)

    def _build_guided_answer(self, payload: UserAgentRequest) -> str | None:
        if not self._is_generic_expense_prompt(payload):
            return self._build_implicit_expense_draft_guidance(payload)

        attachment_names = self._resolve_attachment_names(payload)
        attachment_hint = ""
        if attachment_names:
            attachment_hint = (
                f" 我已带入 {len(attachment_names)} 份附件名称，但目前还不能直接读取附件内容，"
                "仍需要你补充关键信息。"
            )

        return (
            "可以帮你发起报销。请补充费用类型、发生时间、金额、事由和相关对象，"
            "或者直接上传票据附件，我再继续帮你判断能否报、缺什么材料以及生成报销草稿。"
            f"{attachment_hint}"
        )

    def _build_implicit_expense_draft_guidance(
        self,
        payload: UserAgentRequest,
    ) -> str | None:
        if not self._is_implicit_expense_draft_request(payload):
            return None

        amount_text = next(
            (item.value for item in payload.ontology.entities if item.type == "amount"),
            "",
        )
        expense_type = next(
            (
                EXPENSE_TYPE_LABELS.get(item.normalized_value, item.value)
                for item in payload.ontology.entities
                if item.type == "expense_type"
            ),
            "报销",
        )
        time_text = payload.ontology.time_range.raw or "本次"
        amount_hint = f"，金额 {amount_text}" if amount_text else ""

        return (
            f"已识别到一笔{time_text}的{expense_type}支出{amount_hint}。"
            "如果要继续生成报销草稿，还需要补充客户单位、参与人员、费用明细和票据附件。"
            "你也可以继续上传发票或图片，我会把这些信息带入后续对话。"
        )

    def _generate_answer_with_model(
        self,
        payload: UserAgentRequest,
        *,
        citations: list[UserAgentCitation],
        suggested_actions: list[UserAgentSuggestedAction],
        risk_flags: list[str],
        draft_payload: UserAgentDraftPayload | None,
        fallback_answer: str,
    ) -> str | None:
        messages = self._build_model_messages(
            payload,
            citations=citations,
            suggested_actions=suggested_actions,
            risk_flags=risk_flags,
            draft_payload=draft_payload,
            fallback_answer=fallback_answer,
        )
        return self._sanitize_model_answer(
            self.runtime_chat_service.complete(
                messages,
                max_tokens=420,
                temperature=0.2,
            )
        )

    def _sanitize_model_answer(self, answer: str | None) -> str | None:
        if not answer:
            return None

        cleaned = re.sub(r"<think>.*?</think>", "", answer, flags=re.DOTALL | re.IGNORECASE)
        cleaned = cleaned.strip()
        return cleaned or None

    def _build_model_messages(
        self,
        payload: UserAgentRequest,
        *,
        citations: list[UserAgentCitation],
        suggested_actions: list[UserAgentSuggestedAction],
        risk_flags: list[str],
        draft_payload: UserAgentDraftPayload | None,
        fallback_answer: str,
    ) -> list[dict[str, str]]:
        facts = {
            "run_id": payload.run_id,
            "user_message": payload.message,
            "ontology": payload.ontology.model_dump(mode="json"),
            "context": {
                "entry_source": payload.context_json.get("entry_source"),
                "user_name": payload.context_json.get("name"),
                "user_role": payload.context_json.get("role"),
                "request_context": payload.context_json.get("request_context"),
                "attachment_count": payload.context_json.get("attachment_count"),
                "attachment_names": self._resolve_attachment_names(payload),
            },
            "tool_payload": payload.tool_payload,
            "citations": [item.model_dump(mode="json") for item in citations],
            "suggested_actions": [
                item.model_dump(mode="json") for item in suggested_actions
            ],
            "risk_flags": risk_flags,
            "draft_payload": (
                draft_payload.model_dump(mode="json")
                if draft_payload is not None
                else None
            ),
            "selected_capability_codes": payload.selected_capability_codes,
            "requires_confirmation": payload.requires_confirmation,
            "fallback_answer": fallback_answer,
        }

        system_prompt = (
            "你是企业财务共享场景中的中文智能助手，负责和最终用户直接对话。"
            "你只能基于提供的事实回答，不能编造制度、流程结果或附件内容。"
            "如果用户问题很笼统，例如“我要报销”，优先告诉用户你可以协助什么，"
            "并明确要求补充费用类型、金额、时间、事由、参与对象或上传票据。"
            "如果上下文里只有附件名称，必须明确说明你只拿到了附件名称，"
            "不能假装已看过图片、PDF 或发票内容。"
            "不要声称已经提交、审批、付款、入账或真正执行了任何动作；如果只是建议、草稿或待确认，要明确说清楚。"
            "若给出了风险标签、制度引用或建议动作，可以简洁吸收进回答，但不要新增未提供的事实。"
            "只输出最终给用户看的自然语言，不要输出 JSON、Markdown、标题、"
            "<think> 标签或任何中间推理。"
            "使用简体中文，控制在 2 到 4 句。"
        )
        user_prompt = (
            "请根据以下事实生成最终答复，优先保持准确、具体、可执行：\n"
            f"{json.dumps(facts, ensure_ascii=False, indent=2)}"
        )
        return [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_prompt},
        ]

    def _build_query_answer(self, payload: UserAgentRequest) -> str:
        scenario = payload.ontology.scenario
        data = payload.tool_payload
        subject = self._resolve_subject(payload)

        if scenario == "expense":
            record_count = int(data.get("record_count") or 0)
            total_amount = float(data.get("total_amount") or 0)
            return (
                f"{subject}共命中 {record_count} 笔报销，金额合计 {total_amount:.2f} 元。"
                "如需继续处理，可以查看明细或生成处理意见草稿。"
            )

        if scenario == "accounts_receivable":
            record_count = int(data.get("record_count") or 0)
            outstanding_amount = float(data.get("outstanding_amount") or 0)
            return (
                f"{subject}共命中 {record_count} 条应收，未回款金额 {outstanding_amount:.2f} 元。"
                "建议结合账龄和客户分布继续排查逾期风险。"
            )

        if scenario == "accounts_payable":
            record_count = int(data.get("record_count") or 0)
            outstanding_amount = float(data.get("outstanding_amount") or 0)
            return (
                f"{subject}共命中 {record_count} 条应付，待付金额 {outstanding_amount:.2f} 元。"
                "如需推进动作，建议先生成付款建议草稿并发起人工确认。"
            )

        return "已完成当前查询，但暂时没有更多结构化结果可展示。"

    def _build_explain_answer(
        self,
        payload: UserAgentRequest,
        citations: list[UserAgentCitation],
    ) -> str:
        if citations:
            titles = "、".join(item.title for item in citations[:2])
            summary = citations[0].excerpt or "请结合制度全文进一步确认。"
            return f"已检索到相关依据：{titles}。核心说明：{summary}"

        return (
            f"当前还没有与“{SCENARIO_LABELS.get(payload.ontology.scenario, '当前问题')}”"
            "强匹配的已上线规则引用，建议先人工复核或补充更具体的单据上下文。"
        )

    def _build_risk_answer(
        self,
        payload: UserAgentRequest,
        citations: list[UserAgentCitation],
    ) -> str:
        risk_flags = self._resolve_risk_flags(payload)
        if not risk_flags:
            return "当前未识别到明确风险标签，建议继续查看原始明细或补充更多上下文。"

        reasons = [RISK_REASON_MAP.get(flag, f"{flag} 需要人工进一步确认。") for flag in risk_flags]
        citation_text = (
            f" 参考规则：{'、'.join(item.title for item in citations[:2])}。"
            if citations
            else ""
        )
        return (
            f"本次识别到 {len(risk_flags)} 类风险：{'、'.join(risk_flags)}。"
            f"触发原因：{'；'.join(reasons)}。"
            "建议先复核明细、附件和审批链，再决定是否继续处理。"
            f"{citation_text}"
        )

    def _build_draft_payload(self, payload: UserAgentRequest) -> UserAgentDraftPayload:
        scenario_label = SCENARIO_LABELS.get(payload.ontology.scenario, "业务")
        subject = self._resolve_subject(payload)
        title = f"{scenario_label}处理意见草稿"
        body = (
            f"主题：{subject}\n"
            "结论：已根据当前语义解析结果生成草稿，尚未自动执行。\n"
            "建议：请先核对明细、规则命中和所需附件，再由人工确认是否提交正式流程。\n"
            f"原始问题：{payload.message}"
        )
        return UserAgentDraftPayload(
            draft_type=payload.ontology.scenario,
            title=title,
            body=body,
            confirmation_required=True,
        )

    def _build_suggested_actions(
        self,
        payload: UserAgentRequest,
    ) -> list[UserAgentSuggestedAction]:
        if self._is_generic_expense_prompt(payload):
            return [
                UserAgentSuggestedAction(
                    label="上传票据",
                    action_type="ask_clarification",
                    description="上传发票、行程单或付款截图，继续识别报销内容。",
                ),
                UserAgentSuggestedAction(
                    label="补充报销信息",
                    action_type="ask_clarification",
                    description="补充费用类型、金额、时间和事由后继续处理。",
                ),
            ]

        if payload.ontology.intent in {"query", "compare"}:
            return [
                UserAgentSuggestedAction(
                    label="查看明细",
                    action_type="open_detail",
                    description="继续查看命中记录和过滤条件。",
                ),
                UserAgentSuggestedAction(
                    label="生成处理意见",
                    action_type="create_draft",
                    description="把当前查询结果整理成可确认草稿。",
                ),
            ]

        if payload.ontology.intent == "risk_check":
            return [
                UserAgentSuggestedAction(
                    label="人工复核风险",
                    action_type="manual_review",
                    description="优先检查明细、附件和规则命中原因。",
                ),
                UserAgentSuggestedAction(
                    label="生成整改建议",
                    action_type="create_draft",
                    description="把风险说明整理成处理意见草稿。",
                ),
            ]

        if payload.ontology.intent == "draft":
            return [
                UserAgentSuggestedAction(
                    label="复制草稿",
                    action_type="copy_draft",
                    description="复制当前草稿后交由人工确认。",
                ),
                UserAgentSuggestedAction(
                    label="补充上下文",
                    action_type="ask_clarification",
                    description="补充单据编号、客户或供应商信息以完善草稿。",
                ),
            ]

        return [
            UserAgentSuggestedAction(
                label="查看规则全文",
                action_type="open_rule",
                description="继续查看引用规则或知识内容。",
            ),
            UserAgentSuggestedAction(
                label="补充问题上下文",
                action_type="ask_clarification",
                description="补充业务对象、时间或单据范围，提升回答准确度。",
            ),
        ]

    def _build_rule_citations(self, payload: UserAgentRequest) -> list[UserAgentCitation]:
        domain = self._resolve_domain(payload.ontology.scenario)
        items = self.asset_service.list_assets(
            asset_type=AgentAssetType.RULE.value,
            status=AgentAssetStatus.ACTIVE.value,
            domain=domain,
        )
        ranked = self._rank_rule_assets(items, payload)
        citations: list[UserAgentCitation] = []
        for item in ranked[:2]:
            detail = self.asset_service.get_asset(item.id)
            if detail is None:
                continue
            excerpt = self._extract_excerpt(str(detail.current_version_content or ""))
            citations.append(
                UserAgentCitation(
                    source_type="rule",
                    code=detail.code,
                    title=detail.name,
                    version=detail.current_version,
                    updated_at=detail.updated_at.date().isoformat(),
                    excerpt=excerpt,
                )
            )
        return citations

    @staticmethod
    def _resolve_risk_flags(payload: UserAgentRequest) -> list[str]:
        tool_flags = payload.tool_payload.get("risk_flags")
        if isinstance(tool_flags, list) and tool_flags:
            return [str(item) for item in tool_flags]
        return [str(item) for item in payload.ontology.risk_flags]

    @staticmethod
    def _resolve_subject(payload: UserAgentRequest) -> str:
        named_entities = [
            item.value
            for item in payload.ontology.entities
            if item.type in {"employee", "customer", "vendor", "project"}
        ]
        if named_entities:
            return f"{'、'.join(named_entities)} 相关数据"
        return f"{SCENARIO_LABELS.get(payload.ontology.scenario, '当前')}场景数据"

    @staticmethod
    def _is_generic_expense_prompt(payload: UserAgentRequest) -> bool:
        if payload.ontology.scenario != "expense":
            return False
        normalized_message = re.sub(r"\s+", "", payload.message)
        return normalized_message in GENERIC_EXPENSE_PROMPTS

    @staticmethod
    def _is_implicit_expense_draft_request(payload: UserAgentRequest) -> bool:
        if payload.ontology.scenario != "expense" or payload.ontology.intent != "draft":
            return False

        compact_message = re.sub(r"\s+", "", payload.message)
        if any(keyword in compact_message for keyword in EXPLICIT_DRAFT_KEYWORDS):
            return False

        return True

    @staticmethod
    def _resolve_attachment_names(payload: UserAgentRequest) -> list[str]:
        names = payload.context_json.get("attachment_names")
        if not isinstance(names, list):
            return []
        return [str(name) for name in names if str(name).strip()]

    @staticmethod
    def _resolve_domain(scenario: str) -> str | None:
        if scenario == "expense":
            return "expense"
        if scenario == "accounts_receivable":
            return "ar"
        if scenario == "accounts_payable":
            return "ap"
        return None

    @staticmethod
    def _rank_rule_assets(
        items: list[AgentAssetListItem],
        payload: UserAgentRequest,
    ) -> list[AgentAssetListItem]:
        def score(item: AgentAssetListItem) -> tuple[int, str]:
            tags = {str(value) for value in item.scenario_json or []}
            weight = 0
            if payload.ontology.scenario in tags:
                weight += 3
            if payload.ontology.intent in tags:
                weight += 2
            for risk_flag in payload.ontology.risk_flags:
                if risk_flag in tags:
                    weight += 4
            return weight, item.code

        ranked = sorted(items, key=score, reverse=True)
        return [item for item in ranked if score(item)[0] > 0]

    @staticmethod
    def _extract_excerpt(content: str) -> str:
        lines = [line.strip() for line in str(content).splitlines() if line.strip()]
        cleaned: list[str] = []
        for line in lines:
            normalized = re.sub(r"^[#>\-\*\d\.\s`]+", "", line).strip()
            if normalized:
                cleaned.append(normalized)
            if len(cleaned) >= 2:
                break
        return "；".join(cleaned[:2])